Stop me if you’ve heard this one: a digital analyst, with a background in web development and marketing, takes a role heading up web analytics for a Fortune 500 company...and finds himself in the midst of chaos. The business wants to know how their marketing campaigns are performing, and they keep pestering IT for a more nuanced analysis. Meanwhile, tech wants normalized, better-quality data, and labels the lack of these inputs a “marketing problem.” Enter the analyst, trying to steer marketing in the direction of better data capture and IT toward a better understanding of marketing’s challenges -- all while advocating within the global organization for a greater focus and investment in the very data capture and analysis that these stakeholders have grown to mistrust.

Looking at the world of campaign analytics in 2017, it can be challenging for anyone who didn’t grow up in the industry to make sense of its complexity. Seasoned analysts and marketers have a history with the technology, but they've often witnessed so much change so quickly that it can feel at times like someone snuck up and piled a bunch of new challenges on top of old ones, before solutions to the old problems were fully worked out.When it comes to URL tracking and campaign analytics, the tools at our fingertips are impressively precise. Not that long ago, the only data you could meaningfully derive from a referring URL was how much traffic you’re getting from various websites. At a high level it allowed companies to see which partnerships and publishing platforms were bringing eyes to their sites, but that’s about it.

In one of hisOmnitureCare mailbag blog posts, Adobe Analytics guru Ben Gaines was asked about weirdness in Classification reports. With scarcely any details, Ben guessed that the Adobe client was using Sub-Classifications, and recommended they turn them off. Within that response, he launched a semi-explanation for/semi-diatribe against Sub-Classifications, ending one paragraph with the outburst: What’s the point?

Picture a Thousand Words (i.e., Make a Chart)

Adobe Analytics clients are genuinely surprised to learn how far off the mark their own reports have strayed. SAINT Classification technology isn't rocket science—anyone who has used a Pivot table or a Lookup function in Excel is capable of getting their head fully around the deep magic involved. I could tell people a thousand times that their reports might not bear scrutiny, but instead let me make the case with four pictures that will do the job better.I was preparing a Tracking First introduction for a client in early January who asked that I use some of his own data for the demo. He sent me a SAINT classification file, and it served really well for the presentation; Tracking First easily detected their preferred style for creating and classifying their codes. Glancing at the spreadsheet itself, however, I saw that it contained many codes that should have been classified but clearly weren't, and so I decided to dig a little deeper and analyze how well this specific SAINT table was being maintained.

Most Used, Least Understood

SAINT Classifications are extremely familiar—many would say all too familiar—among Adobe Analytics/Omniture experts. Although this technology has existed in its present form for over a decade, it remains the most highly-frequented technology within Adobe Analytics reporting system. This insight was provided by Adobe Senior Product Manager John Bates, who at the 2014 Adobe Analytics conference in Utah acknowledged SAINT Classifications as the "most-used feature within Adobe Analytics".Surprisingly, however, there are many misconceptions about this technology, and a dearth of best practices concerning its application. This article is the first in a series of educational posts I'll be publishing over the next few months aimed at remedying that situation.

Backstory

This morning on the Yahoo Web Analytics forum a question was posted about best practices for campaign tracking when companies are using both Google Analytics and Omniture. This particular company was apparently switching from GA to Adobe Analytics, but I should note that many companies don't only experience this challenge during a transition; many companies place both Omniture and Google Analytics code on their sites and keep them there for the long term.I spent a good portion of the day devising a plan: how I would do it if I were in that situation. I should say that I'm a big fan of campaign tracking (obviously, seeing as I've built a company around tracking code preparation), and I love to push the limits of technology and squeeze as much juice out of its engine as possible. But, in the case of campaigns, I generally lean towards simplicity and automation, because anything you choose to do today, you have to keep doing tomorrow and the day after (if you want your campaign reports to mean anything).My recommendation, at least during the transition phase, would be to mimic precisely the Google Analytics campaign reports within SiteCatalyst using Classifications, and the best news is that you can set it up to be entirely automatic!

No Single Answer is Right for EverybodyThis is the fifth time I’ve tried to write this blog post. It’s just really hard to talk in general terms about code structure, when that structure does (and should) vary greatly from one company to the next.When Omniture released SAINT over a decade ago, they included a custom code generator which is still available in the tool today. Have you ever noticed it? It’s right under the SAINT Classifications link in SiteCatalyst’s Admin menu.But even though it enjoys such a prominent placement, in all my years I’ve never encountered a company that actually uses it to generate their marketing codes.

Too Many Daves (and not enough Dougs)A decade ago, I delivered what I believe was the first-ever class on SAINT. It was early days at Omniture, and I was the seventh Account Manager to be hired. Back then the AM team did all the support as well as the training for SiteCatalyst, long before Client Care existed or the two Dougs took over the Omniture University program.I started the class by reading, in its entirety, the Dr. Seuss poem, "Too Many Daves." I wasn't trying to warm up the crowd; I really felt that Mrs McCave's predicament was central to the concept of classifying key values. If you're not familiar with the poem, the point is that Mrs McCave made the unwise decision to give all of her 23 boys the same name: Dave.

My business partner Mike Baird is a UX genius. He drives me crazy. While I'm trying desperately to build a product that works in beta, he'll say something nutty like this: "Instead of focusing on what our product needs the user to do, let's talk about what the user wants to do with the product." That's actually a direct quote from two nights ago.He was talking about the step where the user defines the pattern for their new codes. Admittedly, it's the most confusing piece of the puzzle, because marketers don't want to think about how the tracking codes are formed, they just want a new tracking code. Just like I don't want to know the etymology of the word "cheesecake"; I just want cheesecake. Specifically, I want a slice of that turtle cheesecake they have down the street at Kneaders Café. Are they still open at 10pm on a Thursday night?

Seriously, It's Not That ComplicatedAdobe Omniture's SAINT tool is pretty basic: it's a way to organize your campaign initiatives. If you're sending out your 150th newsletter today, you might want to know if it will be your most successful newsletter ever, so it needs a new tracking code that's different from the 149 newsletters that went before. But somebody else in the organization may want to know how much traffic came from all of the newsletters put together.That's where SAINT comes in. You have one report where each newsletter gets its own value, and another where each value is the same, i.e., "Newsletter". You upload that table to Adobe, and both business users are going to get what they need.